We operate models across multiple frames utilising the Temporal Segment Network[1]} approach of averaging frame levels predictions over an input clip. To facilitate the efficient learning of temporal features between frames, we utilise the Temporal Shift Module[2]} which is inserted in every residual block for all models.
